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From "Apache Spark (JIRA)" <j...@apache.org>
Subject [jira] [Assigned] (SPARK-16710) SparkR spark.glm should support weightCol
Date Mon, 25 Jul 2016 13:37:20 GMT

     [ https://issues.apache.org/jira/browse/SPARK-16710?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Apache Spark reassigned SPARK-16710:
------------------------------------

    Assignee: Apache Spark

> SparkR spark.glm should support weightCol
> -----------------------------------------
>
>                 Key: SPARK-16710
>                 URL: https://issues.apache.org/jira/browse/SPARK-16710
>             Project: Spark
>          Issue Type: Improvement
>          Components: ML, SparkR
>            Reporter: Yanbo Liang
>            Assignee: Apache Spark
>
> Training GLMs on weighted dataset is very important use cases. Users can pass argument
{{weights}} to specify the weights vector in native R. For {{spark.glm}}, we can pass in the
{{weightCol}} which is consistent with MLlib.



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